R/play_stats_per_possesion.R

In AdvancedBasketballStats: Advanced Basketball Statistics

#' @title Play stats per possesion
#' @description The function allows the calculation of the statistics per game projected to P possesions.
#' @param df1 Should be a Data Frame that represents the play's statistics. The parameter has to be in the format provided by the play_data_adjustment() function.
#' @param df2 Should be a Data Frame that represents the team's statistics. The parameter has to be in the format provided by the team_stats() function.
#' @param df3 Should be a Data Frame that represents the rival's statistics. The parameter has to be in the format provided by the team_stats() function.
#' @param p Should be a  number. This parameter has to be the number of possessions to which you want to project the statistics.
#' @param m should be a number. This parameter has to be the duration of a single game.
#' @details The statistical projection is made from the estimation of the possessions that the team plays when the player is on the court.
#' @author Fco Javier Cantero \email{fco.cantero@@edu.uah.es}
#' @author Juan José Cuadrado \email{jjcg@@uah.es}
#' @author Universidad de Alcalá de Henares
#' @return Data frame with statistics by game projected to the possesions entered
#' @examples
#'
#' df1 <- data.frame("Name" = c("Sabonis ","Team"), "GP" = c(62,71),
#' "PTS" = c(387,0), "FG" = c(155,1), "FGA" = c(281,1),
#' "FGA Percentage" = c(0.552,1),"3P" = c(6,1),"3PA" = c(18,1),
#' "3P Percentage" = c(0.333,1),"2P" = c(149,0),"2PA" = c(263,0),
#' "2P Percentage" = c(0.567,0),"FT" = c(39,1),  "FTA" = c(53,1),
#' "FT Percentage" = c(0.736,1),  "ANDONE" = c(12,1), "AST" = c(0,1),
#' "TOV" = c(27,1))
#'
#' df2 <- data.frame("G" = c(71), "MP" = c(17090), "FG" = c(3006),
#' "FGA" = c(6269),"Percentage FG" = c(0.48), "3P" = c(782),
#' "3PA" = c(2242), "Percentage 3P" = c(0.349),  "2P" = c(2224),
#' "2PA" = c(4027), "Percentage 2P" = c(0.552), "FT" = c(1260),
#' "FTA FG" = c(1728),  "Percentage FT" = c(0.729), "ORB" = c(757),
#' "DRB" = c(2490),"TRB" = c(3247),"AST" = c(1803),"STL" = c(612),
#' "BLK" = c(468),   "TOV" = c(1077),  "PF" = c(1471),
#' "PTS" = c(8054),  "+/-" = c(0))
#'
#' df3 <- data.frame("G" = c(71), "MP" = c(17090), "FG" = c(2773),
#' "FGA" = c(6187),"Percentage FG" = c(0.448), "3P" = c(827),
#' "3PA" = c(2373), "Percentage 3P" = c(0.349),  "2P" = c(1946),
#' "2PA" = c(3814), "Percentage 2P" = c(0.510), "FT" = c(1270),
#' "FTA FG" = c(1626),  "Percentage FT" = c(0.781), "ORB" = c(668),
#' "DRB" = c(2333),"TRB" = c(3001),  "AST" = c(1662),"STL" = c(585),
#' "BLK" = c(263),   "TOV" = c(1130),  "PF" = c(1544),
#' "PTS" = c(7643),  "+/-" = c(0))
#'
#' p<- 100
#'
#' m <- 48
#'
#' play_stats_per_possesion(df1,df2,df3,p,m)
#'
#' @export
#'

play_stats_per_possesion <- function(df1,df2,df3,p,m){
  tm_poss  <- df2[1,4] - df2[1,15] / (df2[1,15] + df3[1,16]) * (df2[1,4] - df2[1,3]) * 1.07 + df2[1,21] + 0.4 * df2[1,13]
  opp_poss <- df3[1,4] - df3[1,15] / (df3[1,15] + df2[1,16]) * (df3[1,4] - df3[1,3]) * 1.07 + df3[1,21] + 0.4 * df3[1,13]
  pace     <- m * ((tm_poss + opp_poss) / (2 * (df2[1,2] / 5)))
    play_poss <- (pace/m) * df1[6]
    for(i in 3:ncol(df1)){
      if(i==6||i==9||i==12||i==15){
        df1[i]<- round(df1[i],3)
      }
      else{
        df1[i] <- round((df1[i]/play_poss) * p,2)
      }
    }
    names(df1) <- c("Name","GP","PTS","FG","FGA","FG%","3P","3PA","3P%","2P","2PA","2P%","FT","FTA","FT%","And One","AST","TOV")

  df1[is.na(df1)] <- 0
  return(df1)
}